1. Field of the Invention
The present invention relates to implementation of a Channel Estimator in a wireless receiver, for example a IEEE 802.11a based Orthogonal Frequency Division Multiplexing (OFDM) receiver.
2. Background Art
Local area networks historically have used a network cable or other media to link stations on a network. Newer wireless technologies are being developed to utilize OFDM modulation techniques for wireless local area networking applications, including wireless LANs (i.e., wireless infrastructures having fixed access points), mobile ad hoc networks, etc. In particular, the IEEE Standard 802.11a, entitled “Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications: High-speed Physical Layer in the 5 GHz Band”, specifies an OFDM PHY for a wireless LAN with data payload communication capabilities of up to 54 Mbps. The IEEE 802.11a Standard specifies a PHY system that uses fifty-two (52) subcarrier frequencies that are modulated using binary or quadrature phase shift keying (BPSK/QPSK), 16-quadrature amplitude modulation (QAM), or 64-QAM.
Hence, the IEEE Standard 802.11a specifies an OFDM PHY that provides high speed wireless data transmission with multiple techniques for minimizing data errors.
A particular concern in implementing an IEEE 802.11a based OFDM PHY in hardware involves providing a cost-effective, compact device that can be implemented in smaller wireless devices. Hence, implementation concerns typically involve cost, device size, and device complexity.
For example, conventional design approaches for a design equalizer would be to determine an estimate of channel effects on a transmitted signal, and implement equalizer coefficients based on the inverse function of the estimate of the channel effects. In particular, FIG. 1 is a diagram illustrating a frequency based receiver model 10, where a transmitter 12 outputs a frequency modulated signal X(f). The frequency modulated signal X(f) encounters frequency-selective channel distortion H(f) 14 (i.e., fading), and white Gaussian noise N(f) 16. Hence, the wireless signal Y(f) received by the receiver can be characterized by the transfer function:Y(f)=X(f)H(f)+N(f).
A conventional approach to designing a frequency equalizer 18 would involve obtaining an estimate for the channel distortion H(f), and generating an inverse of the channel distortion, such that an estimate X′(f) of the frequency modulated signal X(f) can be obtained by Y(f)/H(f), or equivalently Y(f)*[1/H(f)]. However, the noise N(f) is included in the received wireless signal Y(f), hence using the inverse of the channel distortion this approach may amplify the channel noise N(f) in the equalized signal:X′(f)=[Y(f)−N(f)]*[1/H(f)].
Hence, attempts to equalize the received signal Y(f) may greatly amplify the noise component N(f), to where the amplified noise may even exceed the originally transmitted signal X(f) if the channel distortion value H(f) is small.
Another concern is that an OFDM receiver having equalized the received signal Y(f) may encounter additional distortion due to changes in channel characteristics H(f) over time (t), such that the channel distortion is more accurately characterized as H(f, t). Meanwhile, with more received data, channel tracking can improve the estimation of the channel even if there are little or no changes in the channel character, since the availability of the more received data provides additional information regarding the channel. Hence, channel tracking is necessary to track changes in the channel characteristics H(f, t) over time. Channel tracking may be implemented using various estimation approaches, for example gradient approach, least-mean-squared adaptive approach, Kalman-filter-based approach, etc. In general, an error message is first defined relative to the received signal Y(f) and a predicted signal P(f) that is optimized based on the prescribed design of the OFDM receiver; the error signal and its Euclidean distance is used to find an appropriate correction via some optimization for the current channel estimation.
However, implementation of Euclidean distance calculations is substantially complex because it involves multiplication and square-root calculations. Further, the channel tracking performance and equalizer stability is totally dependent on the optimization for the system design: arbitrary designs risk introducing instability into the OFDM receiver by equalizing the signals to equalized values that do not enable the channel tracking to converge to a stable operation.